Chang-Xue Feng

Robust Tolerance Design With the Integer Programming Approach

The quality loss function incorporates the cost of tolerances, however, it does not consider the manufacturing cost and design constraints. In this paper, a stochastic integer programming (SIP) approach is presented for simultaneous selection of tolerances and manufacturing processes. A direct link between the minimum manufacturing cost and the required level of manufacturing yield is established through the process capability index C pk . As the tolerances in SIP are discrete, the solution generated is acceptable for manufacturing. It is shown that the integer programming models are applicable in the quality loss function and six sigma design approaches. The SIP approach is illustrated with a classical example of nonlinear tolerance design. The comparison of the proposed SIP approach, the Taguchi method, and the conventional mathematical models in tolerance synthesis is presented.

Cost evaluation in design with form features

Reducing the cost of a product at the design stage is more effective than at the manufacturing stage. In this paper, an attempt is presented to quantify the manufacturing cost in feature-based design. Machining form features are classified as simple and complex. The machining cost of a part depends not only on the type of form features, but also on the relationship among the features. This cost is calculated for four different cases: traditional machining, simultaneous machining, simultaneous set-up and changeover, and multiple machine tools. A manufacturing process is represented with a digraph. The feature-based evaluation of manufacturing cost is formulated as the shortest path problem, and a mathematical model as well as an algorithm are presented to determine the minimum cost design alternative.

A structured approach for analysis of design processes

The purpose of this paper is to present a methodology for analyzing and improving design processes. The methodology presented uses a directed graph and the corresponding incidence matrix to represent a design process or the relationship between constraints and variables in a design problem. A qualitative analysis approach (critical analysis and concurrency analysis) Is used to analyze the process structure and improve it without considering the time aspect. The analysis explores a process structure as well as enhances concurrency of the design process. The critical analysis determines potential activities that may delay a design project and provides suggestions for improvement of the design process. A process with higher degree of concurrency is obtained and therefore the product development time should be reduced. Two examples from electronics illustrate the approach proposed. >

Constraint-based design of parts

Abstract The key issues in design for machining are abstraction, classification, representation and checking of machining constraints. The paper proposes an object-oriented classification scheme for machining constraints. Design by machining features that are restricted by machining constraints are considered. The constraints considered in the paper are probably not original; however, their application at an early design stage to achieve a manufacturable design is novel. To date, these known constraints have not been transformed into a meaningful design paradigm. Thus, a mechanism for checking machining constraints at the early stage of design is presented on the basis of a part topology. Algorithms are developed to check related machining constraints for different cases of part topology. Therefore, for each feature, only a limited number of machining constraints need to be checked. The constraint classification scheme and a mechanism for checking constraints have been implemented as a prototype system, CBD, which is coded in C++ on an HP workstation.

Deterministic tolerance synthesis: a comparative study

The problem of the synthesis of discrete tolerances is modelled as a combinatorial optimization problem, which is then solved by an integer programming approach, a design of experiments method, and the Taguchi method. The paper is perhaps the first attempt to apply the DOE and TM approaches to deterministic tolerance synthesis. Although the design of experiments approach and the Taguchi method are statistical tools for the design and analysis of experiments, they are useful in deterministic tolerance synthesis. A comparative study has been conducted to investigate the advantages and disadvantages of the three approaches for solving the problem of the synthesis of discrete tolerances, with the objective of minimizing the manufacturing cost. The research shows that, while the integer programming approach is suitable for solving linear deterministic problem, the design of experiments approach is more appropriate for nonlinear problems, and it can be used to solve probabilistic problem.

Robust Tolerance Synthesis With the Design of Experiments Approach

Design of tolerances impacts quality, cost, and cycle time of a product. Most literature on deterministic tolerance design has focused on developing exact and heuristic algorithms to minimize manufacturing cost. Some research has been published on probabilistic tolerance synthesis and optimization. This paper presents the design of experiments (DOE) approach for concurrent selection of component tolerances and the corresponding manufacturing processes. The objective is to minimize the variation of tolerance stackups. Numerical examples illustrate the methodology. The Monte Carlo simulation approach is used to obtain component tolerances and tolerance stackups. Process shift, the worst case and root sum square tolerance stackup constraints, and setup reduction constraints have been incorporated into the proposed methodology. Benefits of the proposed DOE approach over exact algorithms are discussed.

Robust Tolerance Design for Quality

Design of a product (process) includes system design, parameter design, and tolerance design. Robust design is closely applicable to parameter design and tolerance design. The current literature on robust design has focused on parameter design while the problem of tolerance design has not been adequately covered. The tolerance design literature emphasizes the use of optimization to minimize cost while little attention has been paid to minimizing the sensitivity of tolerances to the variation of manufacturing processes. This paper discusses the application of the design of experiments (DOE) approach to tolerance synthesis to minimize manufacturing variations in a probabilistic case. The DOE approach is illustrated with an example.

Scheduling Models for Setup Reduction

The reduction of setup time has a significant impact on shortening manufacturing cycle time. In this paper, characteristics of setup activities are investigated, and models for sequencing setup activities are discussed. Sequencing setup activities can be modeled as a project scheduling problem. Two basic linear programming models for scheduling setup activities are presented. The models minimize the setup time (in particular, the internal setup time), and make a trade-off between the time and cost of setup activities with limited machining resources and budget. Factorial analysis is used to provide insights into the minimization of internal setup time.